基于改进粒子群算法的分布式智能照明系统

针对现有公共建筑照明系统存在的高成本、分布式与集中式控制结合能力不高、交互性不强等问题，应用智能优化算法，在分布式框架上实现区域协同照明控制。通过采集窗户处照度信息，预测透过窗户的自然光在工作面上产生的照度值，当自然光不足需要人工光源补充时，通过协同配合，各区域利用改进粒子群算法计算出区域内最佳的灯具开度组合，达到均匀照明，实现舒适性与节能的最佳综合。当照明需求改变时，可以通过WEB端进行修改。最后，通过实际办公室模型在DIALux evo上进行仿真验证。在不同照明需求和环境条件下，实验结果表明相较于普通控制方式（全开全关），该方法在节能和舒适度上具有良好的性能，能有效控制工作面照度，各工作面的最大照度误差都在10%之内，控制方案切实可行，具有实用价值。

Distributed Intelligent Lighting System Based on Improved Particle Swarm Optimization Algorithm

Aiming at the problems of the existing lighting system of public buildings, such as high cost, low ability of combination of distributed and centralized control and weak interaction, intelligent optimization algorithm is applied to realize regional collaborative lighting control in distributed framework.??Through illumination information acquisition window, prediction of natural light through the window on the work of illuminance value. When the natural light is insufficient and artificial light source is needed to supplement, the improved particle swarm optimization algorithm is used to calculate the best combination of luminaries'' openness in each region through coordination, so as to achieve uniform lighting and the best integration of comfort and energy saving.?When lighting requirements change, you can modify them on the WEB side.??Finally, a real office model is used for simulation verification on DIALux evo.??Under different lighting requirements and environmental conditions, the experimental results show that compared with the common control method (all on and all off), the method has good performance in energy saving and comfort, and can effectively control the illumination of working face. The maximum illumination error of each working face is within 10%. The control scheme is feasible and has practical value.